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  1. Le_Bagousse-Pinguet, Yoann (Ed.)
    Root production influences carbon and nutrient cycles and subsidizes soil biodiversity. However, the long‐term dynamics and drivers of belowground production are poorly understood for most ecosystems. In drylands, fire, eutrophication, and precipitation regimes could affect not only root production but also how roots track interannual variability in climate. We manipulated the intra‐annual precipitation regime, soil nitrogen, and fire in four common Chihuahuan Desert ecosystem types (three grasslands and one shrubland) in New Mexico, USA, where the 100‐year record indicates both long‐term drying and increasing interannual variability in aridity. First, we evaluated how root production tracked aridity over 10–17 years using climate sensitivity functions, which quantify long‐term, nonlinear relationships between biological processes and climate. Next, we determined the degree to which perturbations by fire, nitrogen addition or intra‐annual rainfall altered the sensitivity of root production to both mean and interannual variability in aridity. All ecosystems had nonlinear climate sensitivities that predicted declines in production with increases in the interannual variance of aridity. However, root production was the most sensitive to aridity in Chihuahuan Desert shrubland, with reduced production under drier and more variable aridity. Among the perturbations, only fire altered the sensitivity of root production to aridity. Root production was more than twice as sensitive to declines with aridity following prescribed fire than in unburned conditions. Neither the intra‐annual seasonal rainfall regime nor chronic nitrogen fertilization altered the sensitivity of roots to aridity. Our results yield new insight into how dryland plant roots respond to climate change. Our comparison of dryland ecosystems of the northern Chihuahuan Desert predicted that root production in shrublands would be more sensitive to future climates that are drier and more variable than root production in dry grasslands. Field manipulations revealed that fire could amplify the climate sensitivity of dry grassland root production, but in contrast, the climate sensitivity of root production was largely resistant to changes in the seasonal rainfall regime or increased soil fertilization. 
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    Free, publicly-accessible full text available May 20, 2025
  2. Abstract

    Climate models predict more frequent, prolonged, and extreme droughts in the future. Therefore, drought experiments varying in amount and duration across a range of biogeographical scenarios provide a powerful tool for estimating how drought will affect future ecosystems. Past experimental work has been focused on the manipulation of meteorological drought: Rainout shelters are used to reduce precipitation inputs into the soil. This work has been instrumental in our ability to predict the expected effects of altered rainfall. But what about the nonrainfall components of drought? We review recent literature on the co-occurring and sometimes divergent impacts of atmospheric drying and meteorological drying. We discuss how manipulating meteorological drought or rainfall alone may not predict future changes in plant productivity, composition, or species interactions that result from climate change induced droughts. We make recommendations for how to improve these experiments using manipulations of relative humidity.

     
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  3. Abstract

    Plant populations are limited by resource availability and exhibit physiological trade‐offs in resource acquisition strategies. These trade‐offs may constrain the ability of populations to exhibit fast growth rates under water limitation and high cover of neighbours. However, traits that confer drought tolerance may also confer resistance to competition. It remains unclear how fitness responses to these abiotic conditions and biotic interactions combine to structure grassland communities and how this relationship may change along a gradient of water availability.

    To address these knowledge gaps, we estimated the low‐density growth rates of populations in drought conditions with low neighbour cover and in ambient conditions with average neighbour cover for 82 species in six grassland communities across the Central Plains and Southwestern United States. We assessed the relationship between population tolerance to drought and resistance to competition and determined if this relationship was consistent across a precipitation gradient. We also tested whether population growth rates could be predicted using plant functional traits.

    Across six sites, we observed a positive correlation between low‐density population growth rates in drought and in the presence of interspecific neighbours. This positive relationship was particularly strong in the grasslands of the northern Great Plains but weak in the most xeric grasslands. High leaf dry matter content and a low (more negative) leaf turgor loss point were associated with high population growth rates in drought and with neighbours in most grassland communities.

    Synthesis: A better understanding of how both biotic and abiotic factors impact population fitness provides valuable insights into how grasslands will respond to extreme drought. Our results advance plant strategy theory by suggesting that drought tolerance increases population resistance to interspecific competition in grassland communities. However, this relationship is not evident in the driest grasslands, where above‐ground competition is likely less important. Leaf dry matter content and turgor loss point may help predict which populations will establish and persist based on local water availability and neighbour cover, and these predictions can be used to guide the conservation and restoration of biodiversity in grasslands.

     
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    Free, publicly-accessible full text available February 1, 2025
  4. Abstract

    The predicted intensification of the North American Monsoon is expected to alter growing season rainfall patterns in the southwestern United States. These patterns, which have historically been characterized by frequent small rain events, are anticipated to shift towards a more extreme precipitation regime consisting of fewer, but larger rain events. Furthermore, human activities are contributing to increased atmospheric nitrogen deposition throughout this dryland region.

    Alterations in rainfall size and frequency, along with changes in nitrogen availability, are likely to have significant consequences for above‐ground net primary production (ANPP) and plant community dynamics in drylands. The conceptual bucket model predicts that a shift towards fewer, but larger rain events could promote greater rates of ANPP in these regions by maintaining soil moisture availability above drought stress thresholds for longer periods during the growing season. However, only a few short‐term studies have tested this hypothesis, and none have explored the interaction between altered rainfall patterns and nitrogen enrichment.

    To address this knowledge gap, we conducted a 14‐year rainfall addition and nitrogen fertilization experiment in a northern Chihuahuan Desert grassland to explore the long‐term impacts of changes in monsoon rainfall size and frequency, along with chronic nitrogen enrichment, on ANPP (measured as peak biomass) and plant community dynamics.

    Contrary to bucket model predictions, small frequent rain events promoted comparable rates of ANPP to large infrequent rain events in the absence of nitrogen enrichment. It was only when nitrogen limitation was alleviated that large infrequent rain events resulted in the greatest ANPP. Furthermore, we found that nitrogen enrichment had the greatest impact on plant community composition under the small frequent rainfall regime.

    Synthesis. Our long‐term field experiment highlights limitations of the bucket model by demonstrating that water and nitrogen availability sequentially limit dryland ecological processes. Specifically, our findings suggest that while water availability is the primary limiting factor for above‐ground net primary production in these ecosystems, nitrogen limitation becomes increasingly important when water is not limiting. Moreover, our findings reveal that small frequent rain events play an important but underappreciated role in driving dryland ecosystem dynamics.

     
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  5. Abstract

    Plant traits can be helpful for understanding grassland ecosystem responses to climate extremes, such as severe drought. However, intercontinental comparisons of how drought affects plant functional traits and ecosystem functioning are rare. The Extreme Drought in Grasslands experiment (EDGE) was established across the major grassland types in East Asia and North America (six sites on each continent) to measure variability in grassland ecosystem sensitivity to extreme, prolonged drought. At all sites, we quantified community‐weighted mean functional composition and functional diversity of two leaf economic traits, specific leaf area and leaf nitrogen content, in response to drought. We found that experimental drought significantly increased community‐weighted means of specific leaf area and leaf nitrogen content at all North American sites and at the wetter East Asian sites, but drought decreased community‐weighted means of these traits at moderate to dry East Asian sites. Drought significantly decreased functional richness but increased functional evenness and dispersion at most East Asian and North American sites. Ecosystem drought sensitivity (percentage reduction in aboveground net primary productivity) positively correlated with community‐weighted means of specific leaf area and leaf nitrogen content and negatively correlated with functional diversity (i.e., richness) on an intercontinental scale, but results differed within regions. These findings highlight both broad generalities but also unique responses to drought of community‐weighted trait means as well as their functional diversity across grassland ecosystems.

     
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    Free, publicly-accessible full text available February 1, 2025
  6. Free, publicly-accessible full text available November 1, 2024
  7. Primary productivity response to climatic drivers varies temporally, indicating state-dependent interactions between climate and productivity. Previous studies primarily employed equation-based approaches to clarify this relationship, ignoring the state-dependent nature of ecological dynamics. Here, using 40 y of climate and productivity data from 48 grassland sites across Mongolia, we applied an equation-free, nonlinear time-series analysis to reveal sensitivity patterns of productivity to climate change and variability and clarify underlying mechanisms. We showed that productivity responded positively to annual precipitation in mesic regions but negatively in arid regions, with the opposite pattern observed for annual mean temperature. Furthermore, productivity responded negatively to decreasing annual aridity that integrated precipitation and temperature across Mongolia. Productivity responded negatively to interannual variability in precipitation and aridity in mesic regions but positively in arid regions. Overall, interannual temperature variability enhanced productivity. These response patterns are largely unrecognized; however, two mechanisms are inferable. First, time-delayed climate effects modify annual productivity responses to annual climate conditions. Notably, our results suggest that the sensitivity of annual productivity to increasing annual precipitation and decreasing annual aridity can even be negative when the negative time-delayed effects of annual precipitation and aridity on productivity prevail across time. Second, the proportion of plant species resistant to water and temperature stresses at a site determines the sensitivity of productivity to climate variability. Thus, we highlight the importance of nonlinear, state-dependent sensitivity of productivity to climate change and variability, accurately forecasting potential biosphere feedback to the climate system.

     
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    Free, publicly-accessible full text available August 29, 2024
  8. Free, publicly-accessible full text available July 1, 2024
  9. The Monsoon Rainfall Manipulation Experiment (MRME) is designed to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, by altering rainfall pulses, and thus soil moisture, that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and frequency will alter grassland productivity, ecosystem processes, and plant community dynamics. Treatments include (1) a monthly addition of 20 mm of rain in addition to ambient, and a weekly addition of 5 mm of rain in addition to ambient during the months of July, August and September. It is predicted that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. In particular, we predict that many small events will increase soil CO2 effluxes by stimulating microbial processes but not plant growth, whereas a small number of large events will increase aboveground NPP and soil respiration by providing sufficient deep soil moisture to sustain plant growth for longer periods of time during the summer monsoon. 
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  10. The Monsoon Rainfall Manipulation Experiment (MRME) is to understand changes in ecosystem structure and function of a semiarid grassland caused by increased precipitation variability, which alters the pulses of soil moisture that drive primary productivity, community composition, and ecosystem functioning. The overarching hypothesis being tested is that changes in event size and variability will alter grassland productivity, ecosystem processes, and plant community dynamics. In particular, we predict that many small events will increase soil CO2 effluxes by stimulating microbial processes but not plant growth, whereas a small number of large events will increase aboveground NPP and soil respiration by providing sufficient deep soil moisture to sustain plant growth for longer periods of time during the summer monsoon.  These data were collected at a meteorological station at the Monsoon Site. 
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